Abstract:Several countries have reduced their energy consumption and greenhouse gas emissions levels in buildings by promulgating laws, formulating standards and instituting certification programs. In this context, Brazil launched an energy efficiency certification for buildings in 2009. This study aimed to analyze the economic viability and potential greenhouse gas emissions reductions associated with the use of solar water heaters in a typical Brazilian dwelling. Solar thermal systems were simulated at different energy efficiency levels and shower water flow rates. It was found that the use of solar water heater, as compared with electric heater without a hot water storage, presented internal return rate of approximately 26% per year, simple payback around 4.5 years; net present value about US$ 2,194.00 and cost of conserved energy around US$ 0.12 kWh -1 . This study also verified that solar water heater use in a typical Brazilian dwelling reduced emissions compared with electric and gas heating by approximately 95 and 256 kgCO2equivalentyear -1 , respectively. The total reduction potential of greenhouse gas emissions by use solar water heaters for the Brazilian residential sector was substantial, around 5.75 million tCO2equivalentyear -1 .

Primeiramente, à Deus, por sempre me iluminar, proteger e guiar os meus caminhos. Aos meus pais, José Helvecio Martins e Leila de A.O. Martins, e aos meus irmãos, Sarah F. A. Martins e Thiago E. A. Martins, pelo amor, pelo incentivo, pelo apoio incondicional, pela união e por todos os momentos felizes. À minha sobrinha Júlia M. Lima, por ser meu exemplo de força e superação e por sempre alegrar os meus dias. Ao meu namorado Luis Felipe S. Santos e à sua família, pelo amor, amizade, carinho, paciência e suporte durante toda a minha caminhada profissional. Ao Prof. Dr. Paulo Cesar Sentelhas, pela amizade, pela confiança depositada, pelos ensinamentos, pelos conselhos, pela paciência e pela oportunidade.

Cotton (Gossypium hirsutum L., variety latifolium Hutch) is produced by more than 60 countries and, despite the quality and multiplicity of its seeds use it is grown mainly for the production of fibers. The quality of the fiber can differ between different production environments, being a key factor in determining the price and quality of cotton destined for textile products. These differences in quality are mainly associated with cultivars and meteorological conditions, which influence the indicative parameters of fiber quality. The knowledge of the factors that condition the quality of the cotton fiber is important for the definition of the regions with potential for the production of superior quality fibers. Thus, as a way to subsidize the production of better quality cotton fibers, this work aimed to identify and classify the factors that interfere with the quality of the cotton fiber. Data from meteorological variables and cotton fiber quality indices of 32 Brazilian cultivars were submitted to Pearson's correlation and cluster analyses. These analyses were performed considering three phases of the cotton cycle: total cycle; last 100 days of the cycle; and last 50 days of the cycle. Finally, the results of correlation and clustering analysis were compared. In general, considering the total cotton cycle, it was possible to obtain better statistical correlations between the meteorological variables and the quality of the cotton fiber.

Drying kinetics of pineapple agro-industrial residues was studied using thin-layer of product at 40℃, 50℃, 60℃ and 70℃, and airflow rate of 1.5 m/s. The diffusion model was modified and fitted to experimental data of moisture ratio of pineapple residue to estimate the diffusion coefficient as function of temperature, and a good fitting of Arrhenius equation was obtained, with a variance explained of 99.98 %. Values of diffusion coefficients varied in the range from 4.82 × 10 −10 m 2 ⁄s to 11.17 × 10 −10 m 2 ⁄s, approximately. A modification was implemented in the Page's equation to include the diffusion effects explicitly, leading to a less empirical and simpler model to describe drying kinetics of pineapple residue. The model presented in this work proved to be adequate to predict drying ratio of pineapple residue, if the material layer thickness is 1.0 cm, under the drying conditions used.